Long Term Goals

  • think about what the field will need "8 years from now" and what scientists want:
    • energies, derivatives of energies (most important)
    • density of states
  • dirac-kohn-sham
  • all-electron with ability to "understandably" switch to PAW
  • ability to handle degenerate states
  • use multigrid for eigensolver (O(N^2)) so we do less orthogonalization (O(N^3)). do orthogonalization on the coarse grid, and don't lose it moving to finer grids. (mid-90's codes avoided this)
  • multi-GPU
  • ability to scale out errors (like early GPAW). limited eventually by machine accuracy. e.g. romberg integration
  • real-space
  • gpu data exchange with GPU-Direct (within node and over IB ... no data exchange through MPI)
  • avoid orthogonalization, use multi-grid instead
  • adaptive grid (treated locally, only interacts with valence electrons)
  • periodic boundary conditions
  • find some small but interesting problems "along the way"

Goals for "May"

  • port matlab code to GPU
  • demonstrate GPU speed for simple H solid
  • start looking for interesting problems, e.g.
    • how to avoid orthogonalization and handle degenerate states
    • how to extrapolate out errors
    • GPU efficiency
  • real space
  • periodic boundary conditions
  • 1 GPU
  • kohn-sham (dirac-kohn-sham too much work, but keep in mind)
  • adaptive grid, all electron
  • multigrid approaches, eigenvalue solver
  • understand todd approach better?
  • make more modular
  • don't build hamiltonian like gpaw to save memory?
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